Category: AI

The Rise AI-based app for crypto trading

On By mehranmuslimiblogIn AI, FintechLeave a comment

Резултат с изображение за ai crypto

Removing volatility from the cryptocurrency market would most likely make it a more attractive mainstream investment. That is the hope of Rise, a fintech software company based in Germany. It plans to use its artificial intelligence (AI)  trading technology in the cryptocurrency markets in a way that will allow users to trade across multiple exchanges.

Currently, Rise algorithms are being used in stock markets, forex and commodities trading and since its foundation in 2012 it has grown its user base, with in excess of $50 million in assets under management. Hedge funds and insurance companies are among the big financial institutions using its products. More importantly, its consumer facing app, UpTick, which is focused on cryptocurrency, has been downloaded 100,000 times since it became available.

Its white paper explains: “The playing field is being levelled for all who join Rise, as well as bolstering the cryptocurrency market itself with data-driven investment strategies that are free of emotional human bias, ignore hype, and avoid the pump and dump marketing or boom and bust cycles that inevitably bring unnecessary risk to the market.”

Rise also believes that human traders looking to make a profit from cryptocurrencies are pretty much running out of time. The firm believes that this sector will go the way of the traditional stock market, where gains are primarily made by using “machines to which access is restricted to a small population of the uber-wealthy.” The Rise app will bring more democracy to the crypto trading environment and enable small investors to participate.

AI in the Rise app

This detailed explanation of how AI will be used in the app comes from the whitepaper (see link above): “In addition to trading manually on multiple crypto exchanges, the Rise platform will also allow users to subscribe to automated trading strategies with Autopilot, powered by the Rise AI. Users will be able to choose algorithms across a variety of risk classes, pick an allocation across any of their connected exchanges and then enable the Rise engine to automatically execute trades. A key feature is that users’ funds will never leave their wallet, which will allow for full control and protection of assets. Users can track returns and start, stop or pause algorithms at any time, directly via the application. Furthermore, users are able to define custom stop-loss levels for each algorithm to match each user’s individual risk preference. The vision with Autopilot is to become the trusted, automated trading companion that allows users to invest like the sophisticated trading elite, right on their mobile phone. “

Rise has a strong team with a competitive edge, so no wonder the company is upbeat about its forthcoming STO in November. What is more we won’t have to wait very long to use the AI-based Rise app – it is launching in the first quarter of 2019.

How to use AI in a small business

On By mehranmuslimiblogIn AI, Big Data, FintechLeave a comment

If you are a small business owner, you may wonder if it is possible to implement AI in your business; you may even feel very challenged by the idea. There is a sense amongst small business owners that AI is only for the big companies, but this is a mistake; there are ways to use it regardless of the size of your company. Furthermore, at some point your competitors will catch on to the idea of AI and then you’ll be left behind, so don’t follow the sheep and keep thinking “I’m too small for AI.”

  1. Use AI to analyse data

Big business obviously has lots of data to analyse and AI is very useful for this, but it can be applied to more modest amounts of data as well. Plus, it is far less expensive than hiring a firm to do the calculations and provide the insights. From determining what keeps customers coming back to your business to helping you discover new market niches, AI is a versatile statistical tool.

  1. Use AI to hire staff

Small companies don’t usually have an HR department, but AI can help you here. For example, AI can determine which of your past hiring practices were the most effective. Other AI applications can discover solid leads in surprising places, and inform recruiters about the details of a candidate’s work history and his or her fit for a particular role.

  1. Get more organised with AI

AI can help with bookkeeping and other housekeeping activities that staff often find monotonous and dull. When AI is used in this way, staff see it as less of a threat to their jobs.

  1. Improve customer service

It has become essential for companies to develop new ways to quickly address their customers’ concerns. This is one of the reasons why Gartner predicts that a quarter of customer service operations will “integrate virtual customer assistant (VCA) or chatbot technology across engagement channels by 2020, up from less than two percent in 2017.”

  1. AI can assist with marketing

An Inc.com survey found that 93 percent of market researchers think AI presents an opportunity for their industry. It eliminates the need for employees to do mechanical tasks; from data preparation to advanced data analysis, which is the most common use of AI.

According to an April 2018 McKinsey report  AI is “likely to have the most substantial impact in marketing and sales.” Therefore, small businesses should start integrating AI now to reach as many consumers as possible in the future.

 

Will AI make us all multi-lingual?

On By mehranmuslimiblogIn AI, Big Data, FintechLeave a comment

It used to be Babel, but then Google Translate appeared and everyone started using it, regardless of the fact that what this tool often gave you was text that nobody could quite understand. And now it appears that tech companies are pouring money into developing Instant Translators. But why are they doing this?

AI language assistants are keen to help us all communicate in any language it seems and it does have an attraction for many people from diverse backgrounds. The race is on for translation in real time and Google, Apple, Amazon and Microsoft are all working on it and it is rumoured that Alexa will soon be able to provide real time translations and compete with Google Assistant. China also has a budding translator in Xiaomi’s Xiao AI.

All this is only possible because rapid advances in software can achieve speech recognition, speech synthesis, neural networks, and machine translation; all f which are necessary for real-time translation.

It makes sense that instant translators are only beginning to mature now, because of the technological advances. But what’s still not clear: why did companies start pouring money into them in the first place, and who will benefit from them?

The answer lies in the way the world is changing. Worldwide, there are now 250 million migrants — people who reside outside of their birth country — according to a recent Pew Research Study.  Plus, more than 60 million Americans speak a language other than English at home. By the middle of this century, all of these migrants stand to benefit from instant translation technology.  This applies to other countries in Europe and to Canada.

Refugees will benefit even more. Some 1.2 million people will be forcibly displaced from their homes in 2018 alone, according to the UN Refugee Agency and an inexpensive instant translation tool could help meet these people’s basic needs.

Ultimately, though, instant translators will help everyone, no matter their linguistic aptitude, and as we travel, language barriers won’t hold us back. So, perhaps there is much to be gained by the investment in AI instant translators.

 

 

 

Building trust in Artificial Intelligence

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Trust is extremely important in human interactions, and it is also a vital element of the relationship between man and machine. Do you trust this software to do what it says? Is this brand of computers reliable than its competitor? Building trust in artificial intelligence (AI) also needs to be addressed.

Jesus Rodriguez, managing partner at Investor Labs, says, “Trust is a dynamic derived from the process of minimizing risk.” There are ways to approach this with software: testing, auditing and documenting all have a role in establishing the reputation of a software product. However, they are more difficult to implement with AI. Rodriguez neatly explains why: “In traditional software applications, their behavior is dictated by explicit rules expressed in the code; in the case of AI agents, their behavior is based on knowledge that evolves over time. The former approach is deterministic and predictable, the latter is non-deterministic and difficult to understand.”

So, what steps can we take to establish and measure trust in AI? At the moment confidence in an Ai product is highly subjective and often acquired without a clear understanding of the AI’s capabilities.

A team at IBM has proposed four pillars of trusted AI: fairness, robustness, explainability and lineage. What does each of them mean?

Fairness

“AI systems should use training data and models that are free of bias, to avoid unfair treatment of certain groups.” Establishing tests for identifying, curating and minimising bias in training datasets should be a key element to establish fairness in AI systems.

Robustness

“AI systems should be safe and secure, not vulnerable to tampering or compromising the data they are trained on.” AI safety is typically associated with the ability of an AI model to build knowledge that incorporates societal norms, policies, or regulations that correspond to well-established safe behaviours.

Explainability

“AI systems should provide decisions or suggestions that can be understood by their users and developers.” We have to know how AI arrives at specific decisions and be able to explain how it got there.

Lineage

“AI systems should include details of their development, deployment, and maintenance so they can be audited throughout their lifecycle.” The history and evolution of an AI model is an important part of building trust in it.

IBM also proposes providing a Supplier’s Declaration of Conformity that helps to provide information about the four key pillars of trusted AI. It’s a simple solution, and although it may not be the ultimate one, it represents progress in the world of AI.